Image-to-Text
Transformers
PyTorch
Safetensors
English
blip-2
visual-question-answering
vision
image-captioning
Instructions to use Salesforce/blip2-opt-2.7b-coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip2-opt-2.7b-coco with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="Salesforce/blip2-opt-2.7b-coco")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Salesforce/blip2-opt-2.7b-coco") model = AutoModelForVisualQuestionAnswering.from_pretrained("Salesforce/blip2-opt-2.7b-coco") - Notebooks
- Google Colab
- Kaggle
Update layer norm eps
#1
by nielsr HF Staff - opened
- config.json +1 -1
config.json
CHANGED
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@@ -210,7 +210,7 @@
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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-
"layer_norm_eps": 1e-
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"length_penalty": 1.0,
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"max_length": 20,
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"min_length": 0,
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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+
"layer_norm_eps": 1e-6,
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"length_penalty": 1.0,
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"max_length": 20,
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"min_length": 0,
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